A typical television commercial, television program, or movie comprises a series of video clips pieced together. For example, if a scene in a television program is being filmed by cameras at three different locations in a room, that particular scene may include a series of video clips wherein each of the clips was originally recorded by one of the three cameras. A particular video clip is normally separated from an adjacent video clip using a common video transitional marker such as a cut, dissolve, or fade. Blank or uniform fields may also be used to provide visual separation between video clips.
As digital storage becomes more economical, owners of rights to video recordings have begun to digitally archive those recordings. Digital archiving allows video owners to easily preserve old video recordings that are in danger of deterioration or destruction. Digital archiving also allows video owners to separate recordings into individual clips for marketing purposes. For example, a clip from a television program or a movie might be used in a television commercial or in an advertisement placed on the Internet. Also, individual video clips might be incorporated into multimedia software. Television news organizations may more easily share digital video recordings that have been divided up into individual video clips.
Separating digitized video recordings into individual video clips can be a costly process. Initially, separation of digitized recordings into individual video clips was performed manually. An operator of specialized equipment and/or software would manually locate the various transitional markers in the digitized video recording and record the position of those transitional markers.
Techniques have also been developed to automatically identify transitional markers in digitized video recordings using computer hardware, computer software, or a combination of both. Unfortunately, existing techniques use global metrics which focus on each individual video image as a whole to determine image to image (often field to field) similarity. These techniques are not as accurate as is desirable because the use of global metrics neglects the local spatial information contained in a video image. Moreover, some existing techniques make various measurements of the RGB color components of a video image. These techniques are not easily adapted to process both black and white and color video recordings.